A closed-loop artificial pancreas based on model predictive control: Human-friendly identification and automatic meal disturbance rejection

Type 1 diabetes is characterized by a lack of insulin production by the pancreas, causing high blood glucose concentrations and requiring external insulin infusion to regulate blood glucose. Continuous glucose sensors can be coupled with continuous insulin infusion pumps to create a closed-loop artificial pancreas. A novel procedure of “human-friendly” identification testing using multisine inputs is developed to estimate suitable models for use in an artificial pancreas. A constrained model predictive control (MPC) strategy is developed to reduce risks of hypo- and hyperglycemia (low and high blood glucose concentration). Meal detection and meal size estimation algorithms are developed to improve meal glucose disturbance rejection when incoming meals are not announced. Closed-loop performance is evaluated through simulation studies of a type 1 diabetic individual, illustrating the ability of the MPC-based artificial pancreas control strategy to handle announced and unannounced meal disturbances.